Doing Your Best When Stakes Are High? Theory and Experimental Evidence

Nicolas Houy, Jean-Philippe Nicolaï () and Marie Claire Villeval
Additional contact information
Jean-Philippe Nicolaï: ETH Zurich

No 9766, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Achieving an ambitious goal frequently requires succeeding in a sequence of intermediary tasks, some being critical for the final outcome, and others not. Individuals are not always able to provide a level of effort sufficient to guarantee success in all the intermediary tasks. The ability to manage effort throughout the sequence of tasks is therefore critical. In this paper we propose a criterion that defines the importance of a task and that identifies how an individual should optimally allocate a limited stock of exhaustible efforts over tasks. We test this importance criterion in a laboratory experiment that reproduces the main features of a tennis match. We show that our importance criterion is able to predict the individuals' performance and it outperforms the Morris importance criterion that defines the importance of a point in terms of its impact on the probability to achieve the final outcome. We also find no evidence of choking under pressure and stress, as proxied by electrophysiological measures.

Keywords: experiment; Morris-importance; Skin Conductance Responses; choking under pressure; critical ability (search for similar items in EconPapers)
JEL-codes: C72 C92 D81 (search for similar items in EconPapers)
Pages: 43 pages
Date: 2016-02
New Economics Papers: this item is included in nep-cbe, nep-exp and nep-gth
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published - revised version published as 'Always doing your best? Effort and performance in dynamic settings' in: Theory and Decision, 2020, 89 (3), 249-286

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Related works:
Working Paper: Doing Your Best when Stakes are High? Theory and Experimental Evidence (2016)
Working Paper: Doing Your Best when Stakes are High? Theory and Experimental Evidence (2016)
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